Triple
T15616227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisa 2 |
E375418
|
entity |
| Predicate | operatingSystem |
P1593
|
FINISHED |
| Object | Lisa OS |
E77071
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lisa OS | Statement: [Lisa 2, operatingSystem, Lisa OS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lisa OS Context triple: [Lisa 2, operatingSystem, Lisa OS]
-
A.
Lisa OS
chosen
Lisa OS was the graphical user interface–based operating system developed by Apple for its early Lisa personal computer, notable for pioneering features like overlapping windows, menus, and a mouse-driven desktop.
-
B.
LILO
LILO is a classic Linux bootloader that was widely used on early Linux distributions to load operating systems at startup.
-
C.
Teclea
Teclea is a genus of flowering plants in the citrus family Rutaceae, native to parts of Africa and known for its aromatic foliage.
-
D.
Jimo
Jimo is a county-level city under the administration of Qingdao in eastern China's Shandong Province, known for its historical heritage and rapidly developing economy.
-
E.
Lanman
Lanman is a surname most notably associated with American philanthropist William K. Lanman Jr., a major benefactor of Yale University.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e980b748190b43c0b650bf1e629 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56dd1e4c819090bf3cd4425b39b7 |
completed | May 9, 2026, 3:46 p.m. |
Created at: April 10, 2026, 4:13 a.m.